In the present study, we developed a new analytical procedure consisting of the digestion of rice using HCl, Cd purification using anion exchange resin, and then determining the Cd content using fluorescence spectroscopy. Digestion with 0.1 M HCl for 10 min at room temperature was sufficient to extract Cd from the ground rice samples. The Cd in the extract was successfully purified in preference to other metals using Dowex 1X8 chloride form resin. Low concentrations of Cd in the eluate could be determined using fluorescence spectroscopy with a fluoroionophore. Overall, the actual limit of quantification value for the Cd content in rice was about 0.1 mg-Cd/kg-rice, which was sufficiently low compared with the regulatory value (0.4 mg-Cd/kg-rice) given by the Codex Alimentarius Commission. We analyzed authentic brown rice samples using our new analytical procedure and the results agreed well with those determined using inductively coupled plasma optical emission spectrometry (ICP-OES). Since the fluoroionophore recognized Zn In recent years, the contamination of agricultural land by heavy metals, such as cadmium (Cd) , mercury2+ content in rice samples using a solid phase extraction (SPE)-assisted fluorometric paper sensor [2+ using SPE then determined its content using a fluoroionophore immobilized on the test paper. For this method, the limit of detection (LOD) was poor (56 μg-Cd/L-solution) and the digestion method used for pretreating the rice, consisting of microwave irradiation with mixed acid solution, was complicated. Therefore, we have proposed a new analytical procedure consisting of rice digestion, Cd purification, followed by Cd determination using fluorescence spectroscopy as a simple method of analysis for Cd in rice. In the present study, we aim to develop a simple digestion method using 0.1 M HCl, a Cd purification method using anion-exchange resin, then the ratiometric determination of Cd using fluorescence spectroscopy.Currently, the most common analytical procedure for determining the Cd content of rice is a sample pretreatment followed by instrumental analysis using atomic absorption spectrometry (AAS), inductively coupled plasma optical emission spectrometry (ICP-OES), inductively coupled plasma mass spectroscopy (ICP-MS), atomic fluorescence spectrometry (AFS), or electrodes ,13,14,15r sensor . They pu3 (50 mL) then the suspension was gently heated. The suspension was cooled to room temperature then concentrated H2SO4 (2 mL) was added. The suspension was heated again until its color changed to light yellow or colorless. After cooling to room temperature, the solution was transferred to a volumetric flask (100 mL) and 0.1 M HNO3 was made up to the mark. The concentrations of Cd, Zn, Cu and Iron (Fe) were determined using an ICP-OES instrument .Brown rice samples were obtained from rice farmers. The brown rice standard sample (NMIJ CRM 7531-a) was purchased from the National Metrology Institute of Japan . Milli-Q water (18.2 MΩ·cm) was used in all experiments described below. Rice digestion and metal determination were conducted based on Japanese standard method . Briefly, a sample of ground rice (10 g) was added to 10.4 M of HNO3 (1 mL) were added in 10 mL-test tubes then ICP-OES measurements were conducted. The Cd concentration of the extract determined using ICP-OES was compared with that determined by the standard method to evaluate the extraction efficiency.Rice samples (20 g) were ground for 10 s using a laboratory-scale mill . The sample powder was then added to 0.1 M HCl (80 mL) and the mixture stirred at room temperature for 10 min. Following centrifugation at 8000 g for 10 min, the supernatant was filtered through a 1.0-μm-pore-size cellulose ester membrane  to obtain the extract. The extract solution (9 mL) and concentrated HNOWe adopted the method by Kallmann et al.  to purifDowex 1X8 chloride form  was used as the anion-exchange resin. The resin was washed three times with Milli-Q water (10 times the volume of the resin) then soaked in Milli-Q water overnight. A disposable polypropylene column  held the resin. The column was washed with Milli-Q water then filled with 10% ethanol to obtain the surface hydrophilicity of the column. A frit was introduced at the bottom of the column then 0.5 mL of the prepared resin was added to give a column volume (CV) of 0.5 mL. Finally, the resin was capped with another frit then washed with Milli-Q water (20 mL) to remove the ethanol completely. The prepared columns were preserved at 4 °C in a refrigerator before use. For the Cd purification process, water (2 mL) and 0.1 M HCl (5 mL) were passed through the column sequentially before adding the sample. The rice extract solution (40 mL = 80 CV) was passed through the column and the flow-through fraction was obtained. Then, 0.1 M HCl (40 mL = 80 CV) was passed through the column to remove organic compounds and metals (except Cd) to obtain the washout fraction. Finally, water (30 mL = 60 CV) was passed through the column and the Cd was extracted in the elution fraction. The Cd, Zn, Cu, and Fe concentrations of the flow-through, washout and elution fractions were determined using ICP-OES to estimate the elution efficiency.The fluoroionophore, 2,2′:6′,2′′-terpyridine-substituted BODIPY (BDP-TPY), designed in our laboratory, was synthesized according to a previously reported method . The cheRice samples require acid digestion before the metal contents can be determined. In the first step, we optimized the time for grinding the samples. The standard method for rice digestion is complicated and time-consuming. Therefore, we developed a simpler method with fluorescence spectroscopy using 0.1 M HCl solution  which wa− so that the complex was retained on the resin. In contrast, most of the other metals, which were in the free ionic form, passed through the column and collected in the flow-through fraction. During the washout step, 0.1 M HCl solution was passed through the column to remove any residual Zn, Cu, Fe, and organic compounds, especially soluble starch, into the washout fraction. During the elution step, Cd2+ was eluted from the column by passing through Milli-Q water. H2O might exchange chloride anion in the chloro-complex of Cd and convert the Cd complex to free Cd ion, which was then washed out by leaving chloride anion on the column. This was collected in the elution fraction because of the decomposition of the chloro-complex form, which was then analyzed during the following fluorescence determination step. It should be noted that the Cd was purified and its concentration was concentrated 1.33 times during these processes.The rice extract solutions were run through a polypropylene column packed with anion-exchange resin to purify the Cd. As well as the Cd concentration, we determined the Zn, Cu, and Fe concentrations in each column fraction because these other metals may inhibit the determination of Cd when using fluorescence spectroscopy . Figure We determined the Cd and Zn contents in each fraction because Zn can strongly inhibit the determination of Cd using BDP-TPY . The flo2 = 0.978). The LOD (3s/slope) and limit of quantification  values for Cd were determined based on the standard deviations of 11 blank solutions. The LOD and LOQ values were estimated to be 3.8 μg-Cd/L-solution (0.03 μM) and 12.7 μg-Cd/L-solution (0.11 μM), respectively. These values were relatively low compared with those of simple analyses previously reported [We established a calibration curve for Cd by fluorescence spectroscopy with BDP-TPY. Since the fluorescence spectra of BDP-TPY can be affected by pH value due to the protonation reaction , fluoresreported ,20. FurtSince the elution fraction of the rice extract solutions was acidic, we had to optimize the composition of the buffer solution for the fluorescence determination. We investigated the interfering effect of Zn on Cd determination using fluorescence spectroscopy. We then investigated the applicability of fluorescence spectroscopy for measuring the Cd content of rice samples both by the standard method using ICP-OES and by our procedure consisting of HCl digestion, column purification and fluorescence spectroscopy. The Cd contents of fifteen brown rice samples were determined using the standard and our methods , revealiIn the present study, we have developed a simple analytical procedure for determining the Cd content of brown rice samples. We have revealed that digesting a rice sample with 0.1 M HCl for 10 min at room temperature effectively extracted Cd from a ground rice sample. The Cd in the extract was successfully purified in the presence of Zn, Cu, and Fe using a Dowex 1X8 chloride form resin. The Cd content in the elution fraction could be determined using fluorescence spectroscopy with a fluoroionophore with LOD and LOQ values of 3.8 μg-Cd/L-solution and 12.7 μg-Cd/L-solution, respectively. We analyzed authentic brown rice samples using our developed method and the results agreed well with those measured using ICP-OES. Overall, the actual LOQ value for Cd content in brown rice was about 0.1 mg-Cd/kg-rice. Based on these results, we concluded that our developed method would be suitable for the simple screening of the Cd content in rice samples. Nevertheless, as we reported previously, BDP-TPY is a fluoroionophore with high selectivity for Zn, Cd and Hg ions . We also


Human T cell leukemia virus type 1 (HTLV-1) causes adult T cell leukemia (ATL) in a proportion of infected individuals after a long latency period. Development of ATL is a multistep clonal process that can be investigated by monitoring the clonal expansion of HTLV-1-infected cells by isolation of provirus integration sites. The clonal composition  during the latency period in a given infected individual has not been clearly elucidated.We used high-throughput sequencing technology coupled with a tag system for isolating integration sites and measuring clone sizes from 60 clinical samples. We assessed the role of clonality and clone size dynamics in ATL onset by modeling data from high-throughput monitoring of HTLV-1 integration sites using single- and multiple-time-point samples.From four size categories analyzed, we found that big clones  and very big clones  had prognostic value. No sample harbored two or more VB clones or three or more B clones. We examined the role of clone size, clone combination, and the number of integration sites in the prognosis of infected individuals. We found a moderate reverse correlation between the total number of clones and the size of the largest clone. We devised a data-driven model that allows intuitive representation of clonal composition.This integration site-based clonality tree model represents the complexity of clonality and provides a global view of clonality data that facilitates the analysis, interpretation, understanding, and visualization of the behavior of clones on inter- and intra-individual scales. It is fully data-driven, intuitively depicts the clonality patterns of HTLV-1-infected individuals and can assist in early risk assessment of ATL onset by reflecting the prognosis of infected individuals. This model should assist in assimilating information on clonal composition and understanding clonal expansion in HTLV-1-infected individuals.The online version of this article (doi:10.1186/s40246-017-0112-8) contains supplementary material, which is available to authorized users. Clonal expansion in neoplasms is accepted as a general feature of a broad range of tumors and has been addressed from different perspectives –5. DetecIn the clinical setting, the vast amounts of data rapidly generated by NGS technologies require efficient and accurate processing, analysis, management, interpretation, visualization, and conversion to useful knowledge for rendering more accurate patient outcomes . In respTree theory belongs to discrete mathematics , 44 and In total, 60 clinical samples from 29 individuals were used, including 9 cross-sectional samples , 4 longiAcross all samples, a tag system was used to isolate integration sites and measure clone sizes. All details for experimental design and protocols are provided in . In brieWe used clonality data from 60 samples derived from cross-sectional and longitudinal analyses of HTLV-1-infected individuals. Longitudinal monitoring of 21 cases (51 samples) was performed over a period of 15–90 months. Complete patient and sample information is provided in Additional file In total, nine ACs  or chronic) at time point 1 were analyzed, along with follow-up data at time point 2. Seven patients  were SM at time point 1. Of these, five  progressed to the chronic subtype at time point 2, one  progressed to the acute subtype, and one  remained SM. Four patients  were in the chronic state at time point 1. Of these, three  remained chronic and one  progressed to the acute state at time point 2. Individual 21 was an acute patient who was monitored at 4 time points before, during, and after therapy. Finally, clonality data of some cross-sectional samples  were also included.R = –0.55) indicates a moderate negative correlation. Box plots in Fig. P = 0.05 and P = 0.0001, respectively; Fig. P value of the difference between B and VB categories was 0.08  tree  have ten possible members E = {VB-VB, VB-B, VB-S, VB-VS, B-B, B-S, B-VS, S-S, S-VS, VS-VS}. In the proposed tree structures, the key values indicate clone size. To discriminate and visualize clone sizes, different shapes and colors are used. We first provided four basic ordered max-trees based on clone size as primary rules  are represented in Fig. As an example, we present the case of individual 7, who was monitored at four time points over 6 years Fig. . Unlike Individual 6 was an invaluable AC, with two atypically large B clones at time point 1. Therefore, the clonality tree was located in a higher risk area. Consistent with the model, the patient developed SM ATL at time point 2 (H-16) and remained SM at time point 3 (H-18). At time point 4 (H-15), this patient showed a VB clone, a B clone, and an increased proviral load (PVL)  who was monitored at four time points before, during, and after treatment. The absolute sizes of the largest clone at each time point were 2848, 2411, 2147, and 4066 cells, and the integration site was located at chr9:22270886 (–). This clone belonged to the VB group; the patient remained resistant to therapy and ultimately relapsed. The number of background VS and S clones was H-30: 152 VS; H-39: 394 VS, 2 S; H-26: 420 VS, 4 S, and H-55: 21 VS. The number of integration sites fluctuated during therapy but was greatly reduced after relapse  at a non-malignant state gave rise to dominant clones during the malignant disease. None of the samples with only S and VS clones belonged to patients who developed ATL over time. Thus, consistent with what we have reported previously , the cloCombining biological experimental data with computational analysis and mathematical modeling facilitates quantification and accurate description of biological phenomena. Using simpler mathematics is recommended to improve communication with experimental biologists . In geneThe model of ATL clonal expansion presented here permits investigation of the impact of clonal expansion and related parameters on the risk of ATL development by offering a new understanding of how clonality patterns contribute to disease progression. This easy-to-understand model is an appropriate data-driven model for ATL clonality because it uses real biological data without theoretical assumptions and relies on a small number of variables and a simple set of relationships to explain the clonality status of samples.Here, we used tree-based structures to show clonality patterns and to display the importance of clone size and clonal composition in ATL development. This integration site-based clonality tree model (1) has both descriptive and prognostic capacities, (2) provides clear visualization of the results, (3) uses simple mathematics, and (4) is fully data-driven and is not dependent on theoretical assumptions. The proposed hierarchical tree model will be useful for organizing and summarizing a mechanistic understanding of observed results and for providing significant insights into clonal history based on the integration sites of HTLV-1-infected cells. To our knowledge, this is the first model that enables the prediction of prognosis among infected individuals based on clonality information (clone size and dynamics of clones). Designing a scoring system for representing the clonal expansion process and implementing a user-friendly software tool for clinical applications are of high interest for future studies.Additional file 1: Table S1.Sample identification and summary of data. (XLSX 15 kb)Additional file 2: Figure S1.Figure S2. Trees that can represent hierarchical clonal structures based on clone size. Figure S3. Clonality data for longitudinal samples. Figure S4. Clonality data for cross-sectional samples. (PDF 1247 kb)Quality control of sequencing output. Additional file 3: Table S2.Disease status and clonal analysis over time. (PDF 234 kb)


Apolipoprotein A-I (apoA-I) in high-density lipoprotein (HDL) provides cardiovascular protection. Synchrotron radiation circular dichroism (SRCD) spectroscopy was used to analyze the dynamic solution structure of the apoA-I protein in the apo- and HDL-states and the protein structure conversion in HDL formation. Wild-type apoA-I protein was compared to human variants that either are protective  or lead to increased risk for ischaemic heart disease (A164S). Comparable secondary structure distributions in the HDL particles, including significant levels of beta strand/turn, were observed. ApoA-I Milano in HDL displayed larger size heterogeneity, increased protein flexibility, and an altered lipid-binding profile, whereas the apoA-I A164S in HDL showed decrease thermal stability, potentially linking the intrinsic HDL propensities of the variants to disease risk. Other beneficial effects of the apoA-I protein, including its anti-thrombotic and anti-oxidant functions, and a positive influence of apoA-I/HDL on glucose control, with potential implications in the prevention and treatment of diabetes, have also been demonstrated6. These features of the apoA-I protein have spurred large interests in exploring the translational medicine potential in cardiovascular disease and diabetes8.Apolipoprotein A-I (apoA-I) is the main protein component of high-density lipoprotein (HDL) and carries cholesterol and other lipids in blood circulation. The apoA-I protein has a central role in the so-called reverse cholesterol transport pathway where excess cholesterol is removed, e.g., from the vascular wall, and transported back to the liver. This has been described as the major atheroprotective effect of apoA-I9) and can be easily produced in large amounts as recombinant protein from heterologous production systems, its high structure plasticity and large number of hydrophobic amino acids have challenged classical X-ray crystallography approaches. However, X-ray structures from terminally truncated apoA-I proteins have been successfully obtained11. Additional important advances in the structure/function knowledge of apoA-I have been achieved by complementary approaches such as cross-linking combined with mass-spectroscopy16, hydrogen-deuterium exchange17, and electron paramagnetic resonance (EPR) spectroscopy20. For example, the bottom-up EPR approach where information on the local milieu  of individual amino acid side chains are obtained has provided secondary structure maps of lipid-free apoA-I and discoidal 9.6 nm diameter HDL20 and cross-linking experiments have defined intra- and inter-peptide distances in the apoA-I protein16. Still much remains to be defined including the apoA-I protein structure dynamics in the lipid-binding process and how the secondary structure elements  of apoA-I changes, as well as determination of high-resolution structures of the different states of the apoA-I protein.Much attention has also been given to the structural and functional properties of the apoA-I protein, both in the lipid-free and lipid-bound states. Despite apoA-I is a relatively small protein (243 amino acids in the mature protein), it is highly abundant in blood . It was shown that individuals carrying this variant have normal, or better, protection against cardiovascular disease despite low levels of HDL22. Formulations based on the Milano apoA-I protein is tested in clinical trials for coronary artery disease23. On the contrary, an apoA-I variant that was recently identified in a Danish cohort , the A164S variant , was shown to increase the risk of ischeamic heart disease and mortality despite normal levels of apoA-I and HDL24. The molecular basis for how these seemingly minor modifications can have such significant impact on in vivo function and disease risk is still not known.In addition to native apoA-I, several human variants of apoA-I that affect the in vivo phenotypes. To achieve this, we used synchrotron radiation circular dichroism (SRCD) spectroscopy combined with native gel electrophoresis analyses of native/wild-type (WT), Milano and A164S apoA-I proteins in the lipid-free and lipid-bound states. SRCD was specifically chosen over conventional CD spectroscopy as the intense energy in SRCD spectroscopy allows for superior signal-to-noise ratio with negligible influence of the phospholipids on the signal in real-time, and thus for the determination of the secondary structure elements in both the presence and in the absence of phospholipids in a time-dependent manner25.The current study aimed at defining the protein stability and secondary structure distribution of the apoA-I protein in the lipid-bound HDL form, and to follow the dynamic protein structure changes in the lipid-binding process. Specifically, we aimed at determining if these parameters were affected in the protective Milano variant and in the atherogenic A164S variant and if that could explain their Human apoA-I proteins  were produced in a bacterial system, purified by affinity chromatography and treated with TEV protease to remove the affinity purification tag. The purified proteins Fig.  were inc28, and in the lipid-bound HDL state  to reflect monomeric (0.1 mg/ml), dimeric/tetrameric (0.5 mg/ml), and tetrameric/higher order of oligomerization (1.5 mg/ml)ate Fig.  , and 63% alpha-helix, 5% beta strand, 12% turns and 20% unordered structure at a protein concentration of 1.5 mg/ml (multimeric assemblies). In the lipid-bound state the alpha-helix content was 69% , which is lower than that previously observed by conventional CD spectroscopy . The secondary structure distributions of the Milano and A164S proteins were similar to the WT protein, with two main exceptions in the case of the A164S protein. The A164S variant had a lower helical content at 0.1 mg/ml than WT and Milano, and higher alpha helical content in the lipid bound form . No significant differences in the secondary structure composition of WT and Milano were observed when comparing the heterogeneous lipid-bound samples before SEC with the 9.6 nm particles obtained after SEC  we also included the lipid-free data in the comparison. Interestingly, the initial structural changes occurred essentially instantly for the WT and Milano proteins  and the large conformational switch that occurs in the lipid-binding process. Yet, there are limitations in our knowledge about the dynamic behavior of the protein structure, and we also do not have complete knowledge on how clinically relevant amino acid substitutions and modifications affect protein structure and function.32) and lipid-binding lipoproteins . A great advantage with SRCD is that the intense light provided by the synchrotron radiation highly reduces the background absorbance from the buffer constituents and also from the phospholipids, which otherwise is a major obstacle in conventional bench-top CD analyses , and absolutely crucial when studying conformational changes during HDL formation in the presence of phospholipids.To shed light on this, we have here explored the static and dynamic structures of variants of apoA-I that are known to be protective  or atherogenic (A164S) by comparative studies of the proteins in the apo-state, in the lipid-bound HDL-state as well as during the lipid-binding and formation of nascent HDL. SRCD spectroscopy was selected as the preferred method as it allows for in-solution studies on protein secondary structure distribution and also to monitor real-time conformational changes. This method is particularly useful for proteins with high structure plasticity, including intrinsically disordered proteins , corresponding to about 11 amino acids. This is comparable to previous findings based on EPR spectroscopy analyses defining region 40–50, and 149–157, as beta strand structure in the 9.6 nm HDL particles20. The stretch of beta strand structure in region 149–157, which was also defined as a flexible, two-state region in a hydrogen-deuterium exchange mass-spectroscopy study17, would provide additional length to the circumference  and potentially allow for disc size expansion.As was expected all three variants formed DMPC-rHDL particles with a diameter of about 9.6 nm. In addition, a range of larger particle sizes was also formed with the Milano protein  and A164S amino acid substitutions both lead to reduced protein stability in the HDL bound state. However, while the destabilization of the Milano variant is favorable for protein function, the decreased stability of the A164S variant in the HDL particles appears to negatively affect protein functionality. These findings stress the importance of a fine balance of protein structure stability in lipid-binding and exchange, and is informative for the evaluation of compounds aimed at increasing HDL efficacy.31. In short, a bacterial expression system consisting of pEXP-5 plasmid (Novagen) in Escherichia coli strain BL21(DE3) pLysS cells (Invitrogen) was used to produce the apoA-I proteins. His-tagged ApoA-I proteins were purified from bacterial cell lysate by immobilized metal affinity chromatography  under denaturing conditions , pH 7.4). Following binding, an extensive wash with 40 mM imidazole in PBS was performed and proteins were then eluted with 500 mM imidazole in PBS. Imidazole was removed from protein samples by using desalting columns  equilibrated with PBS, pH 7.4, and tobacco etch virus (TEV) protease was employed overnight at 4 °C, in the presence of 1 mM DTT, to remove the His-tag from protein samples. At the end of the incubation, a reverse Ni2+-column step was employed in order purify the cleaved ApoA-I from TEV protease and the His-tag. The flow-through containing cleaved ApoA-I protein was desalted into McIlvaine Buffer  and stored at 4 °C prior to use. SDS-PAGE and Blue-native gel (Invitrogen) were used for analyses of lipid-free protein and HDL particles.ApoA-I WT, Milano (R173C) and A164S proteins were produced and purified as previously described31.Lipid clearance was monitored by monitoring the decrease in the absorbance of the multilamellar vesicles and protein mixture at 325 nm every 10 s for 10 minutes, as previously describedsn-glycero-3-phosphocholine (DMPC)  was dissolved in chloroform:methanol (3:1) which was evaporated under a stream of nitrogen gas and the resulting lipid film was resuspended in McIlvaine buffer. The DMPC emulsion was passed through a polycarbonate membrane with 100 nm pore size using the LiposoFast system . The resulting vesicles were incubated with apoA-I at a 100:1 molar ratio (phospholipid:protein) at 24 °C, in agitation. Samples were taken at 0, 0.5, 1, 3, 6, 9, 12, 24, 96 h and stored at −80 °C in the presence of 10% sucrose prior the Blue Native PAGE analysis, or analysed by SRCD.1,2-dimyristoyl-To isolate the 9.6 nm DMPC lipoparticles, a size-exclusion chromatography (SEC) was employed. SEC was performed by using a preparative Superose 6 increase 10/300 GL column  and samples were eluted in McIlvaine buffer, pH 7, at a flow of 0.5 ml/min. Isolates species were analysed by Native Page, followed by Coomassie staining and Western blot analysis, by using ApoA-I antibodies .38. For the concentration dependence studies, lipid free (LF) ApoA-I protein samples were dialysed against McIlvaine buffer in order to minimize the noise at wavelengths below 200 nm. Protein samples were diluted at 0.1, 0.5 and 1.5 mg/ml, loaded into quartz cuvettes  and the spectra acquired at 25 °C in the far-UV range 185–260 nm, with a 1 nm wavelength increment. Lipid-bound (LB) samples were produced in McIlvaine buffer and analysed by SRCD at 0.5 mg/ml in a 0.2 nm quartz cuvette. All the spectra were corrected subtracting the background signal of the buffer . Secondary structure estimation from CD spectra was carried out using CDApps39 using Continll algorithm with reference data SP 4340. The molar ellipticity ([Θ]) was calculated according to the equation described in41.SRCD experiments were performed using a nitrogen-flushed Module B end-station spectrophotometer, equipped with a 6-cell turret, at B23 Synchotron Radiation CD Beamline at the Diamond Light SourceConcentional CD measurements were performed on a Jasco J-810 spectropolarimeter equipped with a Jasco CDF-426S Peltier, set to 25 °C. Samples were loaded into a 1 mm quartz cuvette and the spectra acquired at 25 °C in the far-UV range 190–260 nm, with a 1 nm wavelength increment.39 and Tm estimated by biphasic fitting using GraphPad Prism 7. The analysis of the secondary structure during the thermal denaturation was performed by using the CONTINLL algorithm with reference data SP 43, between 190 and 260 nm.LB proteins were diluted in McIlvaine buffer at 0.5 mg/ml and placed in a 0.2 mm quartz cuvette. SRCD spectra were collected in 25.1–95.1 °C range, with a 1 °C increment. Results were processed using CDAppsA PCR thermal cycler  was used to denature/renature samples for electrophoretic analysis. The quantification of the species visualized on the gel was performed by using ImageJ software and the amount of each species was plotted as fold change with respect to the total signal.Supplementary data


Escherichia coli, regulates more than 180 genes via two roles: activation and repression. Few methods are available for predicting the regulatory roles from the binding sites of transcription factors. This work proposes an accurate method PredCRP to derive an optimised model (named PredCRP-model) and a set of four interpretable rules (named PredCRP-ruleset) for predicting and analysing the regulatory roles of CRP from sequences of CRP-binding sites. A dataset consisting of 169 CRP-binding sites with regulatory roles strongly supported by evidence was compiled. The PredCRP-model, using 12 informative features of CRP-binding sites, and cooperating with a support vector machine achieved a training and test accuracy of 0.98 and 0.93, respectively. PredCRP-ruleset has two activation rules and two repression rules derived using the 12 features and the decision tree method C4.5. This work further screened and identified 23 previously unobserved regulatory interactions in Escherichia coli. Using quantitative PCR for validation, PredCRP-model and PredCRP-ruleset achieved a test accuracy of 0.96 (=22/23) and 0.91 (=21/23), respectively. The proposed method is suitable for designing predictors for regulatory roles of all global regulators in Escherichia coli. PredCRP can be accessed at https://github.com/NctuICLab/PredCRP.Cyclic AMP receptor protein (CRP), a global regulator in  Escherichia coli (E. coli). CRP was the first purified1, crystallised2, and the most well-studied TF in E. coli9. CRP regulates more than 180 genes10 by cooperating with cAMP. The latter transduces intracellular signals by changing its intracellular concentration in response to environmental signals. Once the concentration of intracellular cAMP changes, the production of the cAMP-CRP complex will be affected14. When the cAMP-CRP complex acts on a binding site for gene regulation, it has one of two opposing regulatory roles: activation or repression15. The CRP-regulated genes are typically involved in energy-related metabolic pathways, such as galactose metabolism, citrate metabolism, and the phosphoenolpyruvate group translocation system16.Cyclic AMP receptor protein (CRP) is one of the most important transcription factors (TFs) in 17. The other category comprise high-throughput methods such as the chromatin immunoprecipitation (ChIP) assay, a sequencing-based method (ChIP-seq)18 and elegant computational methods focusing on predicting TF-binding sites21. Once information on the CRP-binding sites has been obtained, we can further predict the regulatory roles of CRP.To predict the regulatory roles of CRP, we first needed to know more about the CRP-binding site. There are two categories of methods to identify the binding site of a specific TF. One category consists of the low-throughput methods such as the electrophoretic mobility shift assay and the DNase I footprinting assay-lacZ fusion17 and quantitative PCR (qPCR)22. The other consists of a high-throughput approach such as gene expression analysis using RNA-seq23 or microarray data. However, gene expression analysis has a limit in determining indirect effects such as co-expressed but not co-regulated genes24. Currently, the identification of directly co-regulated genes is particularly challenging24. These observations imply that the determination of the regulatory roles of a TF on co-regulated genes is also a challenging problem.There are two approaches to determining regulatory roles of a TF. One is a low-throughput approach such as the promoter27. The Class II rule states that if the CRP-binding site is located at position −41.5, then CRP tends to be an activator27. The Class III rule states that if a CRP-dependent promoter has two or more CRP-binding sites, then the promoter tends to be an activator27. At present, there is no rule linking conditions in the cAMP-CRP complex to it acting as a repressor27.Few methods are available for predicting the regulatory roles of a global TF from TF-binding sequences. The widely used 3-class rules state that if a CRP-binding site satisfies some conditions, CRP tends to be an activator. The Class I rule states that if the CRP-binding site is located at position −61.5, then CRP tends to be an activatorHence, we propose an accurate method, PredCRP, to derive an optimised model (named PredCRP-model) and a set of four interpretable rules (named PredCRP-ruleset) for predicting and analysing the regulatory roles of CRP from given sequences of CRP-binding sites. The design of PredCRP includes four parts see Fig. : (1) est28 . Various prediction models were evaluated to examine both prediction accuracy and interpretation ability. PredCRP-model achieved a training and test accuracy of 0.98 and 0.93, respectively. PredCRP-ruleset covered 88% of the CRP-binding sites and achieved a training accuracy of 0.95. Among the four interpretable rules, the covered binding regions of two activation rules contain the regions of the widely used Class I and II rules of CRP. The other two rules for the repression role are novel and describe the condition relating to the CRP-binding site’s locations and sequence composition. Furthermore, we used PredCRP-model and PredCRP-ruleset to screen and identify 23 previously unobserved regulatory interactions in E. coli and validated these regulatory roles using qPCR experiments. Experimental results showed that 22 and 21 of the 23 interactions were correct using PredCRP-model and PredCRP-ruleset, respectively.As a result, a set of 12 informative features was identified from 380 candidate features of CRP-binding sites using an inheritable bi-objective combinatorial genetic algorithm (IBCGA)Twelve informative features were selected using the IBCGA, which include eight of the 256 4-mer motifs in the composition descriptor  and four features in the location-dependent descriptor: (1) L3: the size of the overlap region between the CRP-binding site and the region from −35 to −10; (2) L6: the size of the overlap region between the CRP-binding site and the region from −10 to 2; (3) L12: the size of the overlap region between the CRP-binding site and the region from −60 to 60; and (4) L15: the size of the overlap region between the CRP-binding site and the region from −95 to −35.Tables To avoid threshold setting bias, we further compared performance in terms of the area under the receiver operating characteristic (ROC) curve (AUC). As shown in Fig. The SVMs with the eight motif features and four location features yielded test accuracy of 0.82 and 0.82, respectively. This result reveals that the use of the 4-mer motifs or location features only cannot produce satisfactory prediction results. Furthermore, the use of a combination of informative motif and location features is important for accurate prediction. PredCRP-model makes the best use of both the informative 4-mer motifs and location features.PredCRP-ruleset has two activation rules and two repression rules obtained from the decision tree method C4.5, along with the 12 informative features. Each extracted interpretable rule corresponds to a specific path from the root to a specific leaf of the decision tree. Each rule has its own cover ratio on the CRPS dataset consisting of 133 activators and 36 repressors. Figure Region, where Region ≤ −49.5 and Region ≥ 49.5, and the number of TTTT motifs is smaller than or equal to 2 in a CRP-binding site, then CRP generally acts as an activator. A1 covers 66.2% (=88/133) of activators in the CRPS dataset and shows an accuracy of 93.6% (=88/94). Furthermore, the binding regions of A1 contain the region of the widely used Class II rule of CRP. The Region ≤ −49.5 of A1 covers 87 activators and the Region ≥ 49.5 covers only one activator.The activation rule 1 (A1) states that if a CRP-binding site is located in binding regions denoted as location variable The activation rule 2 (A2) states that if a CRP-binding site is located in the binding region of −70.5 to −28.5 and there is no AACG motif in the CRP-binding site, then CRP generally acts as an activator. A2 covers 23.3% (=31/133) of activators in the CRPS dataset and shows accuracy of 96.8% (=31/32). Furthermore, the binding region of A2 contains the region of the widely used Class I rule of CRP.Region <70.5 and −49.5 ≤ Region <−10, and there is no TTAC motif in the CRP-binding site, then CRP generally acts as a repressor. R1 covers 38.9% (=14/36) of repressors in the CRPS dataset and shows accuracy of 93.3% (=14/15). The binding region (−49.5 to −10) strongly overlaps with the RNA polymerase-binding site (−35 to −10). On the other hand, the binding region (2 to 70.5) is located downstream of the transcription start site. Therefore, when CRP binds to these regions, it may block the transcription process. The 2 < Region <70.5 of R1 covers five repressors, and the −49.5 ≤ Region <−10 covers nine repressors.The repression rule 1 (R1) states that if a CRP-binding site is located in the binding regions, where 2 < The repression rule 2 (R2) states that if a CRP-binding site is located in the binding region of −31 to 23 and if neither TTAC nor GAGC motif is present in this CRP-binding site, then CRP generally acts as a repressor. R2 covers 19.4% (=7/36) of repressors in the CRPS dataset and shows accuracy of 100% (=7/7). This binding region of −31 to 23 also strongly overlaps with the RNA polymerase-binding site (−35 to −10). Hence, when CRP binds to the region (−31 to 23), it may block the transcription process.ldtB gene in which CRP acts as a repressor based on qPCR validation, but PredCRP-model predicted an activator role. On the other hand, the prediction accuracy of the PredCRP-ruleset is 0.91 (=21/23). The wrong prediction of CRP-binding sites occurred on the ldtB and exuT genes. Based on the qPCR validation, the regulatory roles of CRP acting on the ldtB and exuT genes are repressor and activator, respectively, which PredCRP-ruleset predicted to have opposite roles. The results of the qPCR experiments are shown in Fig. This work utilised the interpretable rules to predict the regulatory roles of CRP acting on 23 CRP-binding sites with weak evidence. The predicted roles of CRP were validated by quantitative PCR experiments. The results show that the prediction accuracy of PredCRP-model is as high as 0.96 (=22/23). The only wrong prediction of CRP-binding sites occurred on the Considering the trade-off between prediction accuracy and interpretation ability, both an SVM model and a set of interpretable rules were proposed. PredCRP-model had a higher accuracy of 0.96 (=22/23) but with less interpretation ability. PredCRP-ruleset obtained satisfactory accuracy of 0.91 (=21/23) and also provides a cover ratio that biologists can easily analyse for the regulatory roles of CRP-binding sites.ldtB was wrongly predicted using PredCRP-model. On the other hand, the regulatory roles of CRP acting on both ldtB and exuT were wrongly predicted using PredCRP-ruleset. The CRP-binding site of ldtB has no informative 4-mer motifs , which satisfies the motif conditions of the four rules. Nonetheless, its location satisfies the A2 rule only. The ldtB gene is annotated with the following GO terms: GO:0006508 (proteolysis), GO:0009252 (peptidoglycan biosynthetic process), GO:0043164 , and GO:0030288 (outer membrane-bounded periplasmic space). These processes take place in the outer-membrane-bounded periplasmic space and may involve more complex regulatory mechanisms rather than the simple blocking mechanism suggested by our two repression rules.The regulatory role of CRP acting on exuT. Similarly, exuT is also annotated with membrane-related GO terms . We assume that exuT may involve more complex activation mechanisms rather than Class I and II mechanisms.On the other hand, both the informative 4-mer motifs TTTT and CATT appeared once on the CRP-binding site of E. coli. First, one can download the dataset of TF-binding sites from RegulonDB, and use the feature extraction programme from https://github.com/NctuICLab/PredCRP. This programme can retrieve the TFs of interest with a given evidence level (strong or weak). Consequently, one can use a similar process like that described in the Materials and Methods section to train a predictor of regulatory roles.The PredCRP method can be applied to predict the regulatory roles of other global regulators in https://github.com/NctuICLab/PredCRP.Figure 29, containing up-to-date information on E. coli. The retrieval procedure of CRPS was given as follows:A dataset (named CRPS) consisting of 169 CRP-binding sites with regulatory roles supported by strong evidence was established to train and evaluate this work. The CRPS dataset was retrieved from the RegulonDB database (version 8.8)Step 1:  Retrieve TF-binding sites where the “TF name” column was annotated with ‘CRP’ from the RegulonDB database.Step 2:  Categorise CRP-binding sites into strong and weak evidence groups using the “evidence” property obtained from the RegulonDB database.Step 3:  Remove redundant CRP-binding sites with the same transcription start site by checking the leftmost and rightmost positions in the genome.Step 4:  Filter out the CRP-binding sites with lengths not equal to 22 base pairs.29. As a result, the CRPS dataset consisting of 169 CRP-binding sites was randomly divided into training and test datasets in a ratio of 2:1, referred to as CRPS-TRN and CRPS-TST, respectively. CRPS-TRN consists of 24 repression sites and 89 activation sites, while CRPS-TST consists of 12 repression sites and 44 activation sites. The CRPS dataset was subsequently used to design and evaluate this work.The strong-evidence group in the RegulonDB v8.8 database is the set of sites selected by performing mutation experiments on TF-binding sitesAn additional dataset (CRPS-TST-2) was used as an independent test for evaluating the PredCRP-model. The CRPS-TST-2 dataset consists of the strong evidence CRP-binding sites that appeared in version 9.4 but not version 8.8 of the RegulonDB database. CRPS-TST-2 contains 12 sites of activation and 8 sites of repression.29: (1) binding in cellular extracts, (2) gene expression analysis, (3) similarity to consensus sequences, (4) reaction blocked in a mutant, (5) inferred by a curator, (6) inferred from a mutant phenotype, and (7) prediction results. The conserved sequence of CRP-binding sites, -NNNTG5TG7ANNNNNNTC16AC18ANNN-, a well-known palindromic sequence, is bound by CRP27. In this consensus sequence, the nucleic acid G at positions 5 and 7 and the nucleic acid C at positions 16 and 18 play crucial roles in providing binding free energy between CRP and the CRP-binding site32. The detailed CRP-binding ability in these four positions is provided in Supporting Information. The consensus sequence criterion can help to determine whether a site is a binding site or not but cannot determine the regulatory roles of CRP directly.To explore the regulatory roles of CRP on all CRP-regulated genes, we enumerated all possible CRP-binding sites and screened putative ones using interpretable rules. The possible CRP-binding sites were first retrieved from the RegulonDB database with weak-evidence annotation (CRPW). The weak evidence was annotated using the following methodsWe selected only the four important sites in which the nucleic acids at positions 5, 7, 16 and 18 were G, G, C, and C, respectively. Consequently, 23 previously unobserved, putative CRP-binding sites with regulatory roles predicted by PredCRP-model and PredCRP-ruleset were identified. Although the 23 putative CRP-binding sites have high probability to be CRP-binding sites according to the consensus sequence criterion, we further proved the 23 sites as CRP-binding sites by referring to the EcoCyc database (see Supporting Information). The 23 predicted CRP-regulated interactions are given in Figure 18, three features from a physicochemical property descriptor, 320 features from the composition descriptors (256 features of 4-mer motif composition descriptor and 64 features of the 3-mer motif composition descriptor), and 40 features from a global sequence descriptor. This work extended the length of CRP-binding sites from 22 to 42 base pairs by respectively adding k base pairs of flanking nucleotides to the regions upstream and downstream of a CRP-binding site for considering interactions within a cis-regulatory region18. In this work, k = 10 was used. The detailed feature extraction is given in Supplementary Information.A comprehensive feature set of CRP-binding sites was established, comprising 380 features, including 17 features from a location-dependent descriptor Table 18, threem informative features from n = 380 features while maximising the prediction accuracy of the SVM classifier using these m features is a bi-objective combinatorial optimisation problem C. To deal with this large parameter optimisation problem, the inheritable bi-objective combinatorial genetic algorithm (IBCGA) was used28. The IBCGA, using an intelligent evolutionary algorithm33, can simultaneously obtain a set of solutions, Sr, where r = rstart, rstart + 1, …, rend in a single run using an inheritance mechanism to efficiently search for the solution Sr+1 to C by inheriting a good solution Sr to C. Sm is the best solution among solutions Sr. The IBCGA can efficiently solve large-scale feature selection problems and is useful for deriving an optimised SVM model35. The intelligent evolutionary algorithm is good at solving large parameter optimisation problems, such as inferring roles within a large-scale quantitative gene regulatory work36.Selecting a minimal set of m selected informative features is evaluated using the following measurements: prediction accuracy (ACC), sensitivity (SEN), specificity, and Matthews’s correlation coefficient37. To provide prediction service to the scientific community, we developed a user-friendly tool based on the SVM model. The detailed algorithm is shown in Supporting Information. The parameter settings of the feature selection module are shown in Table The optimised SVM classifier with the m informative features for predicting the regulatory roles of CRP and CRPS were utilised to develop a rule acquisition method based on the decision tree method C4.538. A set of if-then rules for distinguishing activators from repressors can be derived from the established decision tree. The interpretable if-then rules are used to further elucidate the regulatory roles of CRP.The k-fold cross-validation. The numbers of repressors and activators for training the SVM model are 24 and 89, respectively. To maximise the number of training repressors used, k = 24 was used in this study. The input of the IBCGA is n-dimensional feature vectors of CRP-binding sites with regulatory roles in CRPS-TRN, and the output contains a set of m selected features and an SVM-based classifier with associated parameter settings of γ and C. PredCRP-model is the optimised SVM classifier with the m selected informative features. PredCRP-model is evaluated using the following measurements: prediction accuracy (ACC), sensitivity (SEN), specificity, and Matthews’s correlation coefficient37.In this work, the fitness function of the IBCGA is the prediction accuracy of 39. When E. coli grows in a medium containing glucose, the intracellular cAMP concentration is low40. The DNA-binding ability of CRP is regulated by the cAMP concentration41. A quantitative measurement of CRP-mediated transcriptional regulation was performed by measuring the gene expression level in an E. coli K12 strain lacking the cyaA gene producing endogenous cAMP42, under various cAMP concentrations. Mutant strains used were E. coli BW25113 derivatives generated from the Keio collection system and provided by the National Institute of Genetics of Japan43. The regulatory roles of CRP on a CRP-regulated gene can be determined using the difference between the expression levels of the wild type with the cAMP concentrations of 0 and 1 mM.CRP is a well-known TF governing carbohydrate metabolism22. In this work, the same experimental conditions were used44. RNA isolation was based on the suggested protocol in the TRI Reagent-RNA Kit . RNA samples for quantitative PCR were pre-treated with DNase I . The DNA primers used in the quantitative PCR were designed by Primer Express software  and their complements (Table The quantitative PCR method can obtain expression profiles of genes of interest in a high-throughput and accurate mannerts Table . DNA wasSupporting information


Desulfovibrio caledoniens metabolic activity and its influence on highs trength steel EQ70 were studied by bacterial analyses and electrochemical measurements. The results showed that EQ70 under -0.85 VSCE CP had a higher corrosion rate than that without CP, while EQ70 with -1.05 VSCE had a lower corrosion rate. The enhanced SRB metabolic activity at -0.85 VSCE was most probably caused by the direct electron transfer from the electrode polarized at -0.85 VSCE. This direct electron transfer pathway was unavailable in -1.05 VSCE. In addition, the application of cathodic protection led to the transformation of sulfide rusts into carbonates rusts. These observations have been employed to provide updated recommendations for the optimum CP potential for steel structures in the presence of SRB.Certain species of sulfate-reducing bacteria (SRB) use cathodes as electron donors for metabolism, and this electron transfer process may influence the proper protection potential choice for structures. The interaction between SRB and polarized electrodes had been the focus of numerous investigations. In this paper, the impact of cathodic protection (CP) on  Sulfate-reducing bacteria (SRB) are a major bacterial group involved in microbiologically influenced corrosion (MIC) , 2. The + ions move to the metal surface, where they are adsorbed and reduced as shown in D. caledoniensis Rs, which represents the solution resistance, a chargetransfer resistance (Rct) for the steel specimen surface, a constant-phase element (CPEdl) associated with the electrical double layer, and a Warburg element (W) that represents the diffusion process, which is influenced by the polarized potential. The curves were fitted using ZSimpwin software, with a chi-square (χ2) value less than 0.01. The Rct data analyzed from EIS were calculated by The circuit includes a Rct was indicative of the effects of the polarization potential and the SRB. For the potential range employed in this present study, the Rct value decreased with the negative potential. The Rt,a had the minimum value at -0.85 VSCE. It then began to increase with a decrease in the potential. This suggested that the metal had higher anodic current density than that at OCP, but a lower metal dissolution rate at -0.95 VSCE and -1.05 VSCE.The magnitude of SCE  compounds formed at room temperature. This results in the formation of iron oxides such asFe2O3 and FeOOH, with variations of those iron oxides between different coupons. A low O2/Fe/Cu peak (B.E at 718.6 eV) was only observed on the surface of EQ70 without polarization  and Fe2O3 (B.E at 724.1 eV). When applying the cathodic polarization, O2/Fe/Cu peak (B.E at 718.6 eV) disappeared and the percentage of FeS (B.E at 710 eV)in Fe compounds increased while FeSO4 decreased  were found under cathodic polarization. The iron sulfide precipitation is being cathodically reduced just below a potential of -0.1 VSCE [The sulfur-containing compounds formed on the surface layer of the corrosion product are similar among different treatments. The S spectrum had dominant peak components corresponding to FeSnd FeSO4 . However0.1 VSCE . Peaks i3) were found after applying cathodic polarization. The application of cathodic protection led to the transformation of sulfide rusts into carbonates rusts [The appearance of oxide may be related with the pH increase in solution and the unavoidable oxygen in the experiment. The C-O compound in the O spectra may be related to the bacteria and the EPS . Calciumes rusts .The reaction can be written as:Also other reactions caused an increase in alkalinity that forced a shift in the equilibria of all chemical reactions involving calcium, magnesium, and bicarbonate irons:HCO3−+OSCE, -0.95 VSCE, and -1.05 VSCE. The reaction of H+ to H accelerates as protection potential shift negatively. The SRB metabolic activity was promoted in -0.85 VSCE and -0.95 VSCE versus OCP. If the increase in pH was caused by the consumption of H by SRB as shown in SCE—however, this was exactly the opposite of what was found. The pH at -1.05 VSCE was higher than other systems. The higher pH resulted from the accelerated H production rate leading to redundant OH-. Although some SRB were expected to be efficient oxidizers of hydrogen [2 as a crucial mechanism. They found that corrosive SRB significantly stimulated the cathodic reaction, while non-corrosive yet H2-consuming control SRB had no effect.In this study, the applied potentials were OCP, -0.85 Vhydrogen , there hhydrogen . Hendrikhydrogen conductedG.sulfurreducens were not affected by applied anode potential [In the study by Miriam , the eleotential .G. sulfurreducens strain KN400 than G. sulfurreducens strain DL-1 on graphite anode poised at -0.4 VAg/AgCl was associated with a greater abundance of electrically conductive microbial nanowires—even when growing with the soluble electron acceptor. Thus, the enhanced current density was associated with appropriate selective pressure and clear properties of different bacteria [If SRB could get electrons from proper cathodic polarized electrode more easily than other electron pathways, then it is possible that this electron transfer occurs directly. In the study of Hana , the enhbacteria .Desulfovibrio caledoniensis could obtain electrons from -0.85 VSCE cathodic polarized electrodes more easily than other electron pathways, then it is possible that this process is achieved by specific protein-based structures or conductive nanowires. The easier electron pathway contributed to the enhanced SRB metabolic activity in -0.85 VSCE. The increasing pH can be explained by SCE, the formation of calcareous deposits and the alkaline environment on the surface of polarized steel was not suitable for SRB to obtain electrons from the overly negative polarized electrode and growth. Thus, SRB metabolic activity was restrained at-1.05 VSCE. Saravia reported a dramatic decrease in bacteria settlement and growth by CP in the initial stages of biofilm formation[Similarly, in this study, if the SRB strain formation.SCE CP, while at -1.05 VSCE CP, the SRB metabolic activity was suppressed and EQ70 had a lower corrosion rate. The hypothesis of electron pathway has been proposed according to the experimental data and theory analysis based on a summary of previous research, and requires further research.In theory, the number of SRB and their metabolic activity was considered sufficient to influence microbiological influenced corrosion. Attached microorganisms on the steel surface would accelerate the process of corrosion. The electron transfer resistance also decreased with the formation of nanowires. Thus, SRB metabolic activity was enhanced and EQ70 had a higher corrosion rate at -0.85 VSCE CP and restrained under -1.05 VSCE CP. The electrochemical data showed that the cathodic polarization potential of -0.85 VSCE accelerated the corrosion of EQ70 in SRB medium while -1.05 VSCE inhibited the corrosion. Those results were reinforced by SEM and XPS analysis. The enhanced SRB metabolic activity was most probably caused by the direct electron transfer from the electrode polarized at -0.85 VSCE, and this direct electron transfer pathway was unavailable in -1.05 VSCE.The effect of different cathodic polarization potentials on SRB metabolic activity and its influence on EQ70 corrosion were experimentally demonstrated in this study. The results showed that as the potential became more negative, the pH values of the medium increased due to metabolic activity of SRB. The metabolic activity of SRB was increased below -0.85 VS1 Appendix(DOCX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 FigSCE; c) -0.95 VSCE; and d) -1.05 VSCE.a) OCP; b) -0.85 V(TIF)Click here for additional data file.


An emulsion chemical cross-linking method was used to expediently fabricate pyraclostrobin microcapsules in situ entrapping the pesticide. The loading content and encapsulation efficiency were 18.79% and 64.51%, respectively. The pyraclostrobin-loaded microcapsules showed pH-and thermo responsive release. Microcapsulation can address the inherent limitation of pyraclostrobin that is photo unstable and highly toxic on aquatic organisms. Compared to free pyraclostrobin, microcapsulation could dramatically improve its photostability under ultraviolet light irradiation. Lower acute toxicity against zebra fish on the first day and gradually similar toxicity over time with that of pyraclostrobin technical concentrate were in accordance with the release profiles of pyraclostrobin microcapsules. This stimuli-responsive pesticide delivery system may find promising application potential in sustainable plant protection.Controllable pesticide release in response to environmental stimuli is highly desirable for better efficacy and fewer adverse effects. Combining the merits of natural and synthetic polymers, pH and temperature dual-responsive chitosan copolymer (CS- Pesticides are widely used to improve the production of major crops to meet the global food demand of the escalating population and ensure sustainable development of agriculture. Due to environmental conditions and mode of application, conventional pesticide formulations created a series of serious human health problems and global environmental contamination . ControlThe performance of CRF on controlling the release profile of pesticide is closely related to the carrier materials ,8. To thg-PDMAEMA block copolymers have promising application potential in the agricultural field, especially for controlled pesticide release to address the current challenges that modern pesticides are facing.Among various chemical modifications of CS, graft copolymerization of vinyl monomers onto CS has been shown to be a promising method for chemical and mechanical modification to generate novel properties and functions . Free raN-(2-(1-(4-chlorophenyl)pyrazol-3-yloxymethyl)phenyl) (N-methoxy)carbamate . CS-g-PDMAEMA microcapsule loaded with pyraclostrobin was prepared via an emulsion chemical cross-linking method with glutaraldehyde as a cross-linking agent. The parameters influencing the loading content (LC) and encapsulation efficiency (EE) were studied. The effects of pH and temperature on the release profiles of pyraclostrobin were also studied. Moreover, the photostability improvement of pyraclostrobin in microcapsule as well as the acute toxicity against zebra fish was also demonstrated. In the present study, pH- and temperature-responsive CS-g-PDMAEMA copolymer could be facilely prepared as described in g-PDMAEMA has been used as negatively charged plasmid DNA vectors through formation of polyplexes via electrostatic interaction [g-PDMAEMA copolymer itself through the formation of polymeric micelles via self-assembly, possibly due to the low hydrophobility of PDMAEMA. Taking full advantage of the residual –NH2 group in the skeleton of CS, the emulsion chemical cross-linking method with glutaraldehyde as a cross-linking agent was used to expediently fabricate microcapsule in situ entrapping the pesticide, as indicated by In the present study, free radical polymerization was adopted for modification to endow CS with versatile properties. Due to the excellent biodegradability, biocompatibility, pH- and thermo sensitivities of PDMAEMA copolymers, DMAEMA monomer was used for graft copolymerization of CS initiated by KPS. A CS-eraction . Howeverg-PDMAEMA copolymer and pyraclostrobin microcapsules were further characterized. Fourier transform infrared (FT-IR) spectra of CS, CS-g-PDMAEMA, pyraclostrobin, and Pyr@CS-g-PDMAEMA are shown in g-PDMAEMA  as shown in The morphology and particle size of Pyr@CS-g-PDMAEMA (curve 6b), Pyr@CS-g-PDMAEMA (curve 6c) and pyraclostrobin (curve 6d). CS-g-PDMAEMA has two distinct weight loss stages: the first weight loss at about 50 °C is ascribed to the vaporization of bound water; and the second one started at about 250 °C is due to the thermal decomposition of sample. CS-g-PDMAEMA shows increased weight loss than virgin CS, which is attributed to the fact that the PDMAEMA side chain decomposes to a higher degree than the CS backbone under the same conditions. Pyraclostrobin (curve 6c) shows a sharp weight loss that started at about 200 °C due to its decomposition. The three–stage weight loss in Pyr@CS-g-PDMAEMA is particularly noteworthy. The first stage loss at about 50 °C is ascribed to the vaporization of bound water; the second weight loss at around 200 °C is decomposition of pyraclostrobin and the third weight loss at about 250 °C is primarily attributed to decomposition of CS-g-PDMAEMA, which further proved that CS-g-PDMAEMA were loaded with pyraclostrobin. This weight loss trend was similar to those for N-carboxyethylchitosan-based polyethyl methacrylate graft copolymer. The weight loss increased with the increasing grafting percentages [g-PDMAEMA estimated by TGA data was about 24%. centages . Moreoveg-PDMAEMA carrier in hand, the LC and EE of pyraclostrobin were next optimized including the ratio of carrier-to-pesticide and the amount of cross-linking agent. As shown in With the CS-g-PDMAEMA microcapsule under different thermo and pH conditions.Controllable pesticide releases in response to environmental stimuli are highly desirable for better efficacy and fewer adverse effects. According to the dual-response of the carrier chitosan copolymer, the effects of different pH and temperature on the pyraclostrobin microcapsules release were also studied. 3)2 groups of the grafted polymer, and consequently the intermolecular and intramolecular electrostatic repulsion interactions increase, which facilitates the release of cargo molecules. The similar initial release profiles under different pH values were possibly attributed to the pyraclostrobin near the surfaces of the microcapsules. As time went by, the release rate changed significantly at different pH. The pH-responsive properties of CS-g-PDMAEMA were also verified by CO2-switchable lower critical solution temperatures and turbidity. These effects are associated with the protonation of the tertiary amine group in PDMAEMA by the H2CO3 formed in aqueous solution during CO2 bubbling [The release profile of pyraclostrobin under three different pH values of 3.7, 5.7, and 7.3 at 30 ± 0.5 °C is shown in The effect of temperature on the release profiles of pyraclostrobin from microcapsules was also studied at pH 6.8. A tendency of an increased pesticide release with increasing temperature was observed in k) for pyraclostrobin standard is 0.22 h−1, while k is 0.03 h−1 for microcapsule. The half-life times (t1/2) of photodegradation for pyraclostrobin TC and microcapsule is 3.2 and 23.1 h, respectively, which clearly indicated the increased photostablity by microcapsulation. Compared to free pyraclostrobin, the improved photostability through microcapsulation is possibly due to the fact that microcapsules reduce the probability of the pesticide in direct contact with the incident light. The carrier material not only blocks out the light, but also wraps and controls the release of pyraclostrobin. These results provided that microcapsulation could dramatically improve the photostability of pyraclostrobin, enhance the utilization efficiency and reduce the input of such agriculture chemicals.Pyraclostrobin is unstable under photo irradiation. In order to embody the improved photostability through microcapsulation, the photodegradation of pyraclostrobin microcapsules and 95% pyraclostrobin technical concentrate (TC) as control were investigated under ultraviolet light. The degradation profiles are shown in 50 (24 h) values of 95% pyraclostrobin TC, 25% pyraclostrobin suspension concentrate (SC) and Pyr@CS-g-PDMAEMA were 0.0642, 0.0663, and 0.1020 mg/L, respectively. According to the pesticide toxicity classification standard suggested by the Chemical Pesticide Environmental Safety Evaluation Test Guidelines (GB/T 31270.12-2014), virulence of 95% pyraclostrobin TC, 25% pyraclostrobin SC and Pyr@CS-g-PDMAEMA on zebra fish were extreme toxicity, extreme toxicity, and high toxicity, respectively. Pyr@CS-g-PDMAEMA showed lower toxicity compared with that of control formulations on the first day. These results indicated that the microcapsulation of pyraclostrobin could reduce acute toxicity against zebra fish to some extent. However, the acute toxicity of Pyr@CS-g-PDMAEMA against zebra fish became comparative with that of control formulations over time. The LC50 (96 h) values of 95% pyraclostrobin TC, 25% pyraclostrobin SC and Pyr@CS-g-PDMAEMA were 0.0596, 0.0568, and 0.0674 mg/L, respectively. The acute toxicity test, on the other hand, verified the controlled release of pyraclostrobin from microcapsules. As time went on, most of the pyraclostrobin was released into the solution, resulting in similar toxicity to that of pyraclostrobin TC on the fourth day. The present study opens up the possibility that the acute toxicity of pesticides against fish can be reduced through elaborate process optimization of microcapsulation and precise regulation of pesticide release. During the experiment, no dead or abnormal behaviors were observed in the blank and solvent control groups. After poisoning by pyraclostrobin, a series of toxic symptoms of fish including acute irregular swimming, jumping out of the water, and flipping up and down were observed. When fish die, they finally turn over on their backs. The results of acute toxicity against zebra fish with different pyraclostrobin formulations are shown in Chitosan with the viscosity of 50–800 mPa·s and the average degree of deacetylation of 90% was purchased from Sinopharm Chemical Reagent Co., Ltd. . 2-(Dimethylamino) ethyl 2-methacrylate (DMAEMA) glutaraldehyde, and KPS were purchased from J&K Scientific Ltd. . DMAEMA was purified by distillation under reduced pressure before use. Pyraclostrobin was obtained from Jiangsu Anpon Electrochemical Co., Ltd. . Solvent oil S-200 was kindly provided by Jiangsu Hualun Chemical Industry Co., Ltd. . Hydrochloric acid (HCl), acetone and other chemicals were all of analytical reagent and used as received without further purification. Ultrapure water used in all experiments was prepared using a MilliQ-50 SP reagent water system .v/v) acetic acid under constant stirring until it was completely dissolved. Then, the mixture was heated to 55 °C, and 12 mg of KPS was introduced into the flask while purged with nitrogen. The solution was agitated for 15 min, followed by the addition of 1.0 g of a DMAEMA monomer. The grafting reaction was carried out at 55 °C for 4 h under nitrogen atmosphere. Subsequently, the CS grafted copolymer was precipitated in an excess amount of acetone. DMAEMA homopolymers were removed by refluxing the raw products in acetone for 5 h, and then the purified copolymers were freeze-dried to a constant weight under vacuum to obtain the cotton-like final product, designated as CS-g-PDMAEMA.The free radical polymerization technique was used to synthesise the CS grafted copolymer. Briefly, 3.0 g of CS was dissolved in 150 mL of water with 2% (g-PDMAEMA (0.2 g) was dispersed in 20 mL of 2% acetic acid solution containing 1% (v/v) Tween-80 to form a homogeneous solution at room temperature. To this mixture, a required amount of pyraclostrobin previously dissolved in solvent oil S-200  was added dropwise. The solution was emulsified to form oil-in-water (O/W) emulsion under constant stirring at 5000 rpm for 30 min using a high-speed stirrer . Then, 1 mL of 0.1 M HCl and 1 mL of glutaraldehyde were added into the mixture. After continuing stirring for 10 min, the formed microcapsules were filtered and washed repeatedly with sufficient petroleum ether and water to remove the oil phase as well as an excess of surfactant and unreacted cross-linking agent. A pyraclostrobin encapsulated microcapsule was denoted as Pyr@CS-g-PDMAEMA, which was freeze-dried and stored in a desiccator for further characterization. The amounts of pesticide and glutaraldehyde were optimized to obtain satisfactory encapsulation efficiency (EE) of Pyr@CS-g-PDMAEMA. Microcapsules containing pyraclostrobin were prepared via an emulsion chemical cross-linking method. The above synthesized copolymer CS-For the determination of the pesticide loading content (LC), 20 mg of pesticide microcapsules was fully grinded and extracted with 100 mL of ethanol for 2 h by sonification at room temperature. Then, the microcapsules were centrifuged at 10,000 rpm for 10 min and fitted with a filter (0.45 μm pore size). The amount of pesticide released from the microcapsules in the test solution was analyzed by high performance liquid chromatography  equipped with a diode array detector. The LC (%) of pyraclostrobin and the encapsulation efficiency EE (%) of pyraclostrobin was calculated as follows: LC (%) = (weight of pesticide encapsulated in microcapsules/weight of microcapsules) × 100; EE (%) =  × 100.18 reversed-phase column ; column temperature, 25 °C; mobile phase, (methanol: 0.2% formic acid aqueous solution (v/v) = 40:60), flow rate, 1.0 mL/min, injection volume, 10 μL; and diode array detector (DAD) signals, 295 nm. The operating parameters for HPLC determination were as follows: Venusil XBP-Cg-PDMAEMA, and Pyr@CS-g-PDMAEMA were conducted on a spectrometer  with a potassium bromide pellet. The spectra were collected in the range from 400 to 4000 cm−1 at a resolution of 4 cm−1. The morphological feature and particle size of pesticide microcapsules were characterized with scanning electron microscope  at an accelerating voltage of 10 kV. The 1H-NMR spectra were recorded on a Bruker Avance 300 spectrometer  operating at 300 MHz at room temperature. The samples (15 mg each) were dissolved in 0.7 mL of 1.0 M hydrochloric acid/deuterium oxide (D2O) mixed solvent  and placed in a 5 mm NMR tube. Chemical shifts were referenced to the solvent peak (4.7 ppm for D2O). Fourier transform infrared (FT-IR) spectra of CS, pyraclostrobin, CS-In order to confirm the thermal stability of the grafted copolymers, thermogravimetric analysis (TGA) was performed with a Perkin Elmer Pyris Diamond  from 20 to 550 °C at a heating rate of 15 °C/min under nitrogen atmosphere. TGA was also used to estimate the grafting percentage (G%) using the % residue obtained for chitosan and the grafted copolymers with the following equation: (G%) = (% residue for chitosan − % residue for copolymer/% residue for chitosan) × 100 .v/v/v). The accumulative release profile of pyraclostrobin was calculated by determining the concentration of pyraclostrobin in the release medium at different times. One milliliter of the release medium was withdrawn at a given time intervals for HPLC assay followed by addition of 1 mL of fresh release medium to keep a constant volume. Different pH value  and temperature  were set to investigate the stimuli-responsive release profiles. The accumulative release of pyraclostrobin was calculated according to the following equation [rE was the accumulative release (%) of pyraclostrobin; eV was the volume of sample taken at a given time interval (eV = 1.0 mL); V0 was the volume of release solution (200 mL); nC (mg/mL) is the pyraclostrobin concentration in release medium at time n; pesticidem (mg) was the total amount of pesticide encapsulated in the microcapsules.In addition, 20 mg of microcapsules were dispersed in 2.0 mL of release medium in dialysis bag , which was suspended in 200 mL of release medium in a dissolution tester  at a rotation speed of 100 rpm at 30 ± 0.5 °C. The release medium was composed of phosphate buffer solution (PBS), ethanol and tween-80 emulsifier Er=Vek was the photolysis rate constant, h−1; C0 was the initial concentration of pyraclostrobin in the solution; tC was the residual concentration at time t, mg/L. The half- life time (t1/2) of degradation was calculated when tC was C0/2.Photostability of pesticides has profound impact on their effectiveness. The photostability experiment was conducted on a photochemical reactor . Microcapsules containing 0.4 mg of pyraclostrobin were dispersed in 20 mL of 20% acetonitrile aqueous solution in a quartz tube, which was irradiated by a 500 W high-pressure mercury at room temperature under stirring rate of 100 rpm. 0.8 mL of the mixture was withdrawn at a certain time, and equal volume of the fresh media was added to conserve a constant volume. The sample was extracted by ultrasonic using 0.8 mL of acetonitrile at room temperature for 40 min and fitted with a filter (0.45 μm pore size) for HPLC analysis. For comparison, the photostability of pyraclostrobin technical concentrate was also studied, and the experimental procedure was the same as that for microcapsules. All the treatments were performed three times. The photolysis of pyraclostrobin was characterized by first-order kinetic equation. The calculation formula is as follows:50 values (mg/L) were calculated by software SPSS13.0 . In the present study, acute toxicity was conducted to evaluate the risk of pyraclostrobin against zebra fish by static tests according to the Organisation for Economic Co-operation and Development (OECD) guidelines  and the g-PDMAEMA microcapsules loaded with pyraclostrobin were fabricated via an emulsion chemical cross-linking method with glutaraldehyde as the cross-linking agent. The pyraclostrobin-loaded microcapsules with drug loading of 18.79% showed pH- and thermo responsive release. The cumulative release of pyraclostrobin was higher in acidic medium in comparison with that in basic and neutral solutions. An increase of pesticide release with increasing temperature was obviously observed. Compared to free pyraclostrobin, microcapsulation could dramatically improve its photostability under ultraviolet light irradiation, which provides an alternative strategy for such photo unstable pesticides. Consequently, the utilization efficiency of pyraclostrobin can be enhanced and the input of such agriculture chemical can be decreased. Moreover, microcapsulation could reduce the acute toxicity of pyraclostrobin against zebra fish to some extent on the first day, and reached a similar toxicity to that of pyraclostrobin TC over time. This stimuli-responsive pesticide delivery system may find potential application in sustainable plant protection. In conclusion, CS-


This study examined whether the densities of stem- and enteroendocrine cell progenitors are abnormal in the ileum of patients with irritable bowel syndrome (IBS), and whether any abnormalities in ileal enteroendocrine cells are correlated with abnormalities in stem cells and enteroendocrine cell progenitors.One hundred and one IBS patients covering all IBS subtypes were recruited, and 39 non-IBS subjects were included as a control group. The patients and controls underwent standard colonoscopies, during which biopsy specimens were obtained from the ileum. The biopsy specimens were stained with hematoxylin-eosin and immunostained for Musashi-1 (Msi-1), neurogenin 3 (NEUROG3), chromogranin A (CgA), serotonin, peptide YY (PYY), oxyntomodulin (enteroglucagon), pancreatic polypeptide, and somatostatin. The immunoreactive cells were quantified by computerized image analysis.The densities of Msi-1, NEUROG3, CgA, and serotonin cells were reduced in all IBS patients and in patients with diarrhea-predominant IBS (IBS-D), mixed-diarrhea-and-constipation IBS (IBS-M), and constipation-predominant (IBS-C) relative to the control subjects. While the PYY cell density was increased in IBS-C relative to controls, it did not differ between control subjects and IBS-D and IBS-M patients. The densities of Msi-1 and NEUROG3 cells were strongly correlated with that of CgA cells.The abnormalities in the ileal enteroendocrine cells appear to be caused by two mechanisms: (1) decreases in the clonogenic activity of the stem cells and in the endocrine-cell progenitors differentiating into enteroendocrine cells, and (2) switching on the expression of PYY and switching off the expression of certain other hormones in other types of the enteroendocrine cells. Irritable bowel syndrome (IBS) is a chronic gastrointestinal condition with a prevalence of 5–20% of the world adult population –9. IBS iThe etiology of IBS is unclear, but certain factors appear to play a pivotal role in its pathophysiology, including genetic factors, intestinal bacterial flora, diet, and chronic low-grade intestinal inflammation , 14. AbnMusashi-1 (Msi-1) is localized in gastrointestinal stem cells and their early progenitors, and neurogenin 3 (NEUROG3) is a marker for early intestinal endocrine-cell progenitors –33. It hThe types and densities of endocrine cells differ between the distal and proximal parts of the small intestine, which is probably due to the quite different functions of these two sections of the gastrointestinal tract , 36. WheThis study aimed at examining whether the densities of stem- and endocrine-cell progenitors as manifested by Msi-1 and NEUROG3 are affected in the ileum of patients with IBS. Furthermore, the densities of ileal endocrine cells were measured with the aim of establishing their correlation with possible abnormalities in stem- and endocrine-cell progenitors.One hundred and one patients with IBS according to Rome III criteria , 38 weren = 24) or angiodysplasia (n = 3), or (2) health worries resulting from a relative being diagnosed with colon carcinoma (n = 12).A control group was included that comprised 39 non-IBS subjects  who had undergone colonoscopies because of (1) gastrointestinal bleeding that was found to be due to hemorrhoids  and the BenchMark Ultra IHC/ISH staining module . The sections were incubated with the primary antibodies for 30 min at 37 °C. Details of the primary antibodies used are given in Table 2. The density of endocrine cells was expressed as the number of endocrine cells per square millimeter of epithelium, the density of Msi-1 cells was expressed as the number of immunoreactive cells per crypt, and the density of NEUROG3 cells was expressed as the number of immunoreactive cells per field. Quantification was performed in ten randomly chosen microscopic fields. The measurements were made by the same person (M.E-S.) who was blind to the identities of the slides.Morphometric measurements were performed by applying imaging software  to images obtained with the aid of a computer linked to a microscope  with a camera . The number of immunoreactive cells and the area of the epithelial cells were measured. The numbers of Msi-1, NEUROG3, and endocrine cells in each field were counted manually by pointing and clicking the computer mouse. The area of epithelial cells was determined by manually drawing an enclosed region using the computer mouse. A × 40 objective was used, which resulted in each frame (field) on the monitor representing a tissue area of 0.14 mmP < 0.05 were considered to be statistically significant.Differences in the sex and age distributions between patients and controls were tested using Fisher’s exact test and the Mann-Whitney nonparametric test, respectively. Differences between control subjects, all IBS patients , and IBS-D, IBS-M, and IBS-C patients were tested using the Kruskal-Wallis nonparametric test with Dunn’s posttest. The Kruskal-Wallis test is a nonparametric test that compares three or more unmatched groups, while Dunn’s multiple-comparisons test compares the difference in the sum of ranks between two columns with the expected average difference. Correlations were assessed using the Spearman nonparametric test. The data are presented as mean ± SEM values, and differences for which P = 0.27 and P = 0.67, respectively).The sex and age distributions did not differ significantly between the patients and controls , serotonin, PYY, PP, oxyntomodulin (enteroglucagon), and somatostatin were found in the ileum of all of the subjects , mostly in the crypts. These cells were basket- or flask-shaped, and sometimes had a basal cytoplasmic process.The densities of Msi-1, NEUROG3, CgA, serotonin, and PYY cells are summarized in Table P < 0.001, P < 0.001, P < 0.01, and P < 0.05, respectively). Dunn’s posttest showed that the NEUROG3 cell density was lower in IBS-total, IBS-D, IBS-M, and IBS-C patients than in the controls .The Msi-1 cell density was significantly lower in IBS-total, IBS-D, IBS-M, and IBS-C patients than in the control subjects (P < 0.0001 for both cell types). The CgA and serotonin cell densities were lower in IBS-total, IBS-D, IBS-M, and IBS-C patients than in controls (P < 0.001 for both cell types). The Kruskal-Wallis test revealed significant differences in PYY cell density between controls and IBS-total, IBS-D, IBS-M, and IBS-C patients . Dunn’s posttest showed that the PYY cell density was significantly higher in IBS-total and IBS-C patients than in the control subjects , while it did not differ significantly between IBS-D and IBS-M patients and the control subjects .The Kruskal-Wallis nonparametric test showed significant differences in the CgA and serotonin cell densities between control subjects, IBS-total patients, and IBS-subtype patients   or differentiate into mucosal epithelial cells (differentiation progeny) , 39–52. CgA occurs in all types of enteroendocrine cells –60, withSerotonin cells are the main endocrine cell type in the ileum . The decWhile the density of ileal PYY cells was similar to the control subjects in the IBS-D and IBS-M patients, it was higher in IBS-C patients, which is consistent with previously results obtained in another cohort of IBS patients . It is wIt is difficult to conclude whether the changes in stem and enteroendocrine cells observed in here are primary or secondary to IBS. However, it was hypothesized recently that factors known to play a part in the pathophysiology of IBS—including genetics, diet, the intestinal microbiome, and low-grade inflammation—exert their effects by acting on stem cells and differentiation progeny toward enteroendocrine cells . In otheThe present study confirms the finding of a previous study involving another cohort of IBS patients that the density of enteroendocrine cells is reduced in the ileum . This re